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Convergence of soil nitrogen isotopes across global climate gradients
Joseph M. Craine, Andrew J. Elmore, Lixin Wang, Laurent Augusto, W. Troy Baisden, E. N. Jack Brookshire, Michael D. Cramer, Niles J. Hasselquist, Erik
A. Hobbie, Ansgar Kahmen, et al.
To cite this version:
Joseph M. Craine, Andrew J. Elmore, Lixin Wang, Laurent Augusto, W. Troy Baisden, et al.. Conver-
gence of soil nitrogen isotopes across global climate gradients. Scientific Reports, Nature Publishing
Group, 2015, 5, 8 p. �10.1038/srep08280�. �hal-02635164�
across global climate gradients
Joseph M. Craine1, Andrew J. Elmore2, Lixin Wang3, Laurent Augusto4, W. Troy Baisden5,
E. N. J. Brookshire6, Michael D. Cramer7, Niles J. Hasselquist8, Erik A. Hobbie9, Ansgar Kahmen10, Keisuke Koba11, J. Marty Kranabetter12, Michelle C. Mack13, Erika Marin-Spiotta14, Jordan R. Mayor15, Kendra K. McLauchlan16, Anders Michelsen17, Gabriela B. Nardoto18, Rafael S. Oliveira19,
Steven S. Perakis20, Pablo L. Peri21, Carlos A. Quesada22, Andreas Richter23, Louis A. Schipper24, Bryan A. Stevenson25, Benjamin L. Turner26, Ricardo A. G. Viani27, Wolfgang Wanek23& Bernd Zeller28
1Division of Biology, Kansas State University, Manhattan, KS, 66506, USA,2Appalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, 21532, USA,3Department of Earth Sciences, Indiana University-Purdue University, Indianapolis, IN, 46202, USA,4UMR 1220 TCEM, INRA, Bordeaux Sciences Agro, Villenave d’Ornon, 33883, France,
5National Isotope Centre, GNS Science, Lower Hutt, 5040, New Zealand,6Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT, 59717, USA,7Department of Biological Sciences, University of Cape Town, Rondebosch, 7701, South Africa,8Forest Ecology and Management, Swedish University of Agricultural Sciences (SLU), Umea˚, 90183, Sweden,9Earth Systems Research Center, Morse Hall, University of New Hampshire, Durham, NH, 03824, USA,
10Departement of Environmental Sciences - Botany, Scho¨nbeinstrasse 6, 4056 Basel Switzerland,11Institute of Agriculture, Tokyo University of Agriculture and Technology, Fuchu, Tokyo, 1838509, JAPAN,12British Columbia Ministry of Forests, Lands and Natural Resource Operations, Victoria, British Columbia, V8Z 5J3, Canada,13Department of Biology, University of Florida, Gainesville, FL, 32607, USA,14Department of Geography, University of Wisconsin, Madison, WI, 53706, USA,15Department of Forest Ecology & Management, Swedish University of Agricultural Sciences, Umea˚ 901 83, Sweden,16Department of Geography, Kansas State University, Manhattan, KS, 66506, USA,17Department of Biology, University of Copenhagen, Copenhagen Ø, 2100, Denmark,18Faculdade UnB Planaltina, Universidade de Brası´lia, Brası´lia, 73345-010, Brazil,19Departamento de Biologia Vegetal, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, 13083-862, Brazil,20Forest and Rangeland Ecosystem Science Center, US Geological Survey, Corvallis, OR, 97331, USA,21Universidad Nacional de la Patagonia Austral-INTA-CONICET, Rı´o Gallegos, Santa Cruz, 9400, Argentina,22Coordenaça˜o de Dinaˆmica Ambiental, Instituto Nacional de Pesquisas da Amazonia, Manaus, 69011, Brazil,23Department of Terrestrial Ecosystem Research, University of Vienna, Vienna, 1090, Austria,24Environmental Research Institute, University of Waikato, Hamilton, 3240, New Zealand,25Landcare Research, Hamilton, 3240, New Zealand,26Smithsonian Tropical Research Institute, Balboa, Anco´n, Republic of Panama,27DBPVA, Centro de Cieˆncias Agra´rias, Universidade Federal de Sa˜o Carlos, Araras, SP, 13600-970, Brazil,28Bioge´ochimie des Ecosyste`mes Forestiers, INRA Nancy, Champenoux, 54280, France.
Quantifying global patterns of terrestrial nitrogen (N) cycling is central to predicting future patterns of primary productivity, carbon sequestration, nutrient fluxes to aquatic systems, and climate forcing. With limited direct measures of soil N cycling at the global scale, syntheses of the15N514N ratio of soil organic matter across climate gradients provide key insights into understanding global patterns of N cycling. In synthesizing data from over 6000 soil samples, we show strong global relationships among soil N isotopes, mean annual temperature (MAT), mean annual precipitation (MAP), and the concentrations of organic carbon and clay in soil. In both hot ecosystems and dry ecosystems, soil organic matter was more enriched in
15N than in corresponding cold ecosystems or wet ecosystems. Below a MAT of 9.86C, soild15N was invariant with MAT. At the global scale, soil organic C concentrations also declined with increasing MAT and decreasing MAP. After standardizing for variation among mineral soils in soil C and clay concentrations, soild15N showed no consistent trends across global climate and latitudinal gradients. Our analyses could place new constraints on interpretations of patterns of ecosystem N cycling and global budgets of gaseous N loss.
Q
uantifying global patterns of terrestrial nitrogen (N) cycling is central to predicting future patterns of primary productivity, carbon sequestration, nutrient fluxes to aquatic systems, and climate forcing1–4. With limited direct measurements of soil N cycling at the global scale, past syntheses of the15N514N ratio of soil organic matter (represented asd15N relative to a standard) have inferred that hotter and drier ecosystems SUBJECT AREAS:STABLE ISOTOPE ANALYSIS ECOSYSTEM ECOLOGY
Received 17 June 2014 Accepted 6 January 2015 Published 6 February 2015
Correspondence and requests for materials should be addressed to J.M.C.
(josephmcraine@
gmail.com)
tend to lose a greater proportion of their N through gaseous path- ways5,6. Global soild15N patterns are also among the main evidence used to support the idea that plant productivity in tropical ecosys- tems is less N limited than in temperate ecosystems6,7. These conclu- sions have assumed that soils with highd15N lose a greater proportion of N through strongly15N-discriminating loss processes such as NH3
volatilization and denitrification rather than through less discrim- inating loss pathways such as dissolved organic N and NO32
leaching5,8–10.
Past analyses of global soild15N patterns have examined relatively simple direct relationships between soil d15N and climate or lat- itude5,6,11. Yet, other factors that might affect soild15N and co-vary with climate could influence global relationships between soild15N and climate. For example, a large proportion of the global variation in foliard15N is explained by the N concentrations of leaves12, most likely because plants that have high foliar N concentrations are more likely to be growing in soils where fractionating loss pathways dom- inate N losses. Like leaves, soil C or N concentrations might be important covariates for soild15N. Although rates of microbial pro- cessing of plant litter are known to vary across climate gradients13–15, the extent to which soil C or N concentrations might shape geo- graphic patterns of soild15N remains unexplored. Soils with different C or N concentrations might consistently vary in theird15N due to differences in the composition of organic matter inputs or rates of microbial processing of organic matter, both of which could affect the N isotopic composition of soil organic matter. In addition, soil texture has the potential to affect the relative importance of different loss pathways16 and/or the differential retention of 15N-enriched organic matter17–21. With highly weathered tropical sites more likely to have greater clay concentrations than many high-latitude ecosys- tems22, this may be an additional confounding influence on global patterns of soild15N.
Beyond improving models of the controls on soild15N, it is imper- ative to continue to expand databases of soild15N because non-linear relationships may become apparent as data on soil15N accumulate, which may affect interpolation of N cycling rates in poorly charac- terized ecosystems. For example, at the global scale, foliar d15N increases with increasing foliar N concentrations, but only above a mean annual temperature (MAT) of20.5uC12. Such observations are important, because they prompt mechanistic hypotheses that test critical understanding how climate influences ecosystem N cycling.
For soild15N, past syntheses of soild15N included too few samples, especially for cold ecosystems, to adequately determine whether non- linear relationships exist between soild15N and climate.
To better understand global patterns of soild15N, we assembled a global dataset of published and original surface soild15N values and Figure 1|Map of sites used in this study.Map created in JMP 10.0.2.
Figure 2|Map of climate space of sites in this study to global terrestrial climate density.Sites used in this study are red. Background points represent the density of ice-free land surface area at particular combinations of mean annual temperature (MAT) and mean annual precipitation (MAP).
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Figure 3|Relationships among climate and soil parameters.Relationships between mean annual temperature (MAT) and mean annual precipitation (MAP) and (A,B) soild15N (n5910) and (C,D) soil [C] of surface soils (n5828). Each point represents values for all samples averaged per 0.1u latitude and longitude. The relationship between soil [C] and soild15N is shown in panel (E) (n5828). After accounting for the variation in soild15N explained by soil [C] (n5828), the residual variation in soild15N is shown vs. (F) MAT and (G) MAP (n5828). Gray regression line is not significant atP.0.05. Values displayed in relationships with MAT and MAP were corrected for variation that could be explained by the other climate variable and soil depth.
examined relationships of soild15N with climate, soil organic C and N concentrations ([C], [N]), and soil clay concentrations. The data- set comprised 5824 measurements ofd15N of soil organic matter from surface (,30 cm) mineral soils. Data for an additional 973 organic soils were compiled, but are only analyzed secondarily here asd15N signatures of organic soils are more likely to represent the signatures of plants than the ultimate decomposition products of plant biomass. When averaged at 0.1ulatitude and longitude, soils represented 910 locations (Fig. 1) that spanned 44uC (MAT) (214uC to 30uC) and over 9000 mm mean annual precipitation (MAP) (84–
9510 mm) (Fig. 2).
Results
Congruent with previous research, soil organic matter was more enriched in15N in both hot ecosystems and dry ecosystems than corresponding cold ecosystems or wet ecosystems (Fig. 3; Table 1).
Soild15N increased with increasing MAT at a rate of 0.1860.02%
uC21for soils from ecosystems with MAT.9.8uC. Yet, below 9.8uC, soild15N did not change with increasing MAT (0.035 60.024%
uC21;P.0.1). High-precipitation ecosystems had lower soild15N with soild15N decreasing at a rate of 1.7860.24%per order of magnitude increase in MAP, after accounting for any co-variation in MAT.
Table 1 | Regression results for mineral soild15N vs. climate. Inflection point for MAT in the breakpoint model was 9.8361.83uC. r250.26 for the breakpoint model and 0.24 for the linear model. Units for MAP were mm before log-transformation
Estimate P
Breakpoint
Intercept (%) 7.7160.65 ,0.001
MATCold(%uC21) 0.0360.02 .0.1
MATHot(%uC21) 0.1860.02 ,0.001
log10MAP (%) 21.7860.24 ,0.001
Average Depth (%cm21) 0.0860.02 ,0.001
Linear
Intercept (%) 8.3160.64 ,0.001
MAT (%uC21) 0.1260.01 ,0.001
log10MAP (%) 22.1060.23 ,0.001
Average Depth (%cm21) 0.0960.02 ,0.001
Figure 4|Patterns of soild15N with soil C and N concentrations.Relationships between (A,D) soil carbon concentrations, (B,E) soil nitrogen concentrations, and (C,F) soil C:N with soild15N for (A–C) mineral soils and (D–F) mineral as well as organic soil horizons. For (A–C), each point represents soils averaged for 0.1ulatitude and longitude. All relationships significant atP,0.001.
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At the global scale, soil [C] also declined with increasing MAT and decreasing MAP (P,0.001; r250.42; Fig. 3). Soild15N was highest for low-C soils and decreased with increasing soil [C] (r250.16,P, 0.001, n5828; Fig. 3, Fig. 4). After accounting for variation among mineral soils in soil [C], the global range in MAT observed here was associated with just 2.7%variation in soild15N (Fig. 3), with MAT explaining much less variation in residual soild15N (P,0.001, r25
0.14, n5828). Likewise, after calculating the residuals between soil d15N and [C], MAP no longer predicted variation in soild15N (P5 0.1). Soil [N] and C:N were weaker predictors of soild15N than soil [C], but generate similar patterns as soil [C] (Fig. 4).
The variation in soild15N explained by MAT after taking into account relationships with soil [C] could be caused by the high con- centrations of clay found in many tropical soils. 30% of the residual Figure 5|Relationships between soil carbon concentrations and texture.Shown are the percentages of (A,D) sand, (B,E) silt, and (C,F) clay vs.
(A–C) soil carbon (mg g21) as well as (D–F) residual log10-transformed soil carbon (mg g21) after accounting for MAT, log10MAP, and average depth. All points represent soil values averaged to 0.1ulatitude and longitude.
Figure 6|Patterns of soil clay concentrations with climate.Relationships between (A) mean annual temperature (MAT) and (B) mean annual precipitation (MAP) vs. clay concentrations of surface mineral soils. log (%Clay)5 20.8410.0163MAT10.553log(MAP); r250.47,P,0.001, n5 359. All points represent soil values averaged to 0.1ulatitude and longitude.
variation in soil [C] after accounting for variation in climate could be explained by soil texture (Fig. 5). Soils with greater silt and clay concentrations had greater [C] than sandy soils (Fig. 5). Within our data, hot sites also had greater clay concentrations than cold sites (Fig. 6). After taking into account the positive relationship between clay concentrations and soild15N (Fig. 7), MAT had no remaining influence on soild15N (Fig. 7). Interpretations of these sequential regression results were further supported by a structural equation model that simultaneously evaluated both direct effects of climate on soild15N as well as indirect effects via effects on soil [C] and clay concentrations (Fig. 8). Mean annual temperature and precipitation only influenced soild15N indirectly through their effects on soil [C]
and clay. Direct relationships between climate and soild15N were not significant (Fig. 8).
Discussion
The global-scale relationships between soild15N and both soil [C]
and clay suggest that the relationship between soild15N and climate is indirect, and mediated through climatic effects on soil [C] and clay.
Our analyses indicate that known dependencies of microbial proces- sing of soil C and N on temperature and moisture that have been observed experimentally, within soil profiles, and at local to regional scales23–26largely converge in their effects on soild15N at the global
scale. Further understanding of global soild15N patterns will require direct quantification of the relative importance of different loss path- ways as well as thed15N values and relative quantities of different soil fractions across broad gradients. Among ecosystems, SOMd15N has the potential to be influenced by variation in the15N signature of atmospheric N deposition. Yet, with the signatures of deposited N often near 0%9,27, the lack of pattern in SOMd15N along climate gradients once the degree of decomposition and clay are taken into account is unlikely to be driven by specific regions of the world receiving greater amounts of deposited N.
In all, the global patterns of soild15N revealed here support the hypothesis that hot and/or dry ecosystems might not lose a greater proportion of N to the atmosphere relative to other ecosystems, as has been previously concluded from soil N isotope data5,6. Although the relationships between clay and soild15N could be driven by greater proportions of fractionating gaseous N loss in soils with high clay concentrations, an alternative explanation is the relative propor- tion of fractionating N loss is not directly influenced by clays, but instead is due to clays stabilizing more15N-enriched soil organic matter17–21. As a result of having greater decomposition of organic matter and/or greater concentrations of clay, it is possible that soils in hotter and/or drier ecosystems have soil organic matter with high d15N as a result of having a greater proportion of their N contained in Figure 7|Lack of relationship between climate and soild15N after accounting for variation in clay concentrations.Relationship between (A) clay concentrations in soil and residual soild15N after accounting for the relationship between soild15N and soil [C] (y51.7112.013log(x), r250.22, P,0.001; n5355). Also shown are relationships between (B) mean annual temperature (MAT), (C) mean annual precipitation (MAP) and residual soild15N after accounting for variation in soil [C], clay concentrations, and soil depth. Non-significant relationships are shown in gray. All points represent soil values averaged to 0.1ulatitude and longitude.
Figure 8|Structural equation model of direct and indirect effects of climate on soild15N.Path-diagram of final structural equation model containing only significant relationships.Positive coefficients overlaid on solid paths and negative coefficients on dashed paths. Arrow thickness proportional to path coefficient. Direct effects of climate on soild15N were not significant.
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mineral-associated organic matter as opposed to having a greater proportion of N being lost to fractionating pathways (Fig. 9).
In support of the idea that the proportion of N lost via fraction- ating pathways might not vary predictably across global climate gradients, recent research has revealed underappreciated amounts of N loss to the atmosphere and aquatic ecosystems suggestive of similar proportions of fractionating N losses across climatic gradi- ents. For example, although tundra ecosystems are typically consid- ered dominated by organic N cycling with little net N mineralization28, gross N mineralization rates and N2O fluxes can contribute to a high proportion of losses, especially given seasonal asynchronies between mineralization and uptake29–31. Tropical eco- systems may lose a larger quantity of N to the atmosphere than many temperate ecosystems. Yet, NO32fluxes in tropical streams can also be more than an order of magnitude greater than temperate streams32,33. These examples from geographically disparate ecosys- tems may reflect similar, proportional fractionating losses of N to the atmosphere across latitudinal gradients. Higher N availability that is characteristic of many low-latitude ecosystems may in fact reduce the proportion of N lost in gaseous forms relative to leaching34.
Ultimately, future interpretations of global patterns of N cycling will depend strongly on understanding the mechanisms that drive global relationships between clay content, soil C concentrations and soil organic matterd15N. From these relationships, we hypothesized that global patterns of soild15N may reflect the degree to which soil organic matter has been enriched in15N by microbial processing and protected by mineral association. This would parallel thed15N of soil organic matter consistently increasing with depth across soils glob- ally25, which can be attributed to greater degrees of processing of soil organic matter at depth35–37. Recognizing the influence of the degree of microbial processing and protection on soild15N may potentially alter assumptions that soild15N scales positively with the proportion of N lost via gaseous processes, which has been central to estimates of global denitrification and N2-fixation9,38. Clarifying whether such assumptions are valid is critical. In addition, global patterns of soil d15N need to be rectified with global patterns of plantd15N. For example, it is poorly understood how the relatively high tissue d15N of plants in hot, dry places12relates to our finding that high soil
d15N in these locations is best explained by a high degree of decom- position and protection of organic matter. More research is also needed to understand the mechanisms that explain the different inflection points in plant and soil d15N relationships with mean annual temperature, as well as why plants are generally depleted in
15N relative to soils12. With geographic gradients able to provide a surrogate for future climates39–41, interpretations of global patterns of soild15N will factor prominently in predicting changes in patterns of gaseous N flux to the atmosphere in response to changes in the Earth- climate system.
Methods
Data on soild15N were acquired from the literature and by contacting individual researchers known to have collected soil nitrogen isotope data in the past. For each soil, we collected data on geographic coordinates with climate data taken from the original source or 50-year climatic means (1950–2000) were acquired from WorldClim42. For each soil sample, we recorded soil depth, soild15N, and where possible [C], [N], ratio of C to N on a mass basis, and soil texture (percentages of sand, silt, and clay). Due to correlations among soil texture categories, only clay concen- trations are included in models here.
Only soils considered by the authors as mineral soils (no litter or O horizons) with depths that averaged,30 cm were included in the main synthesis. Select permafrost samples from below this zone were also included, in order to improve the repres- entation of cold sites as there should be little further processing of soil organic matter once frozen. Subsequent analyses also examined patterns across mineral and organic soil horizons. Soils that were under crops were not included in the synthesis.
To reduce over-representation of individual sites, average soild15N were derived for each 0.1ulatitude and longitude. Average soild15N was derived by calculating the averaged15N for each soil depth and then weighting the average soild15N by N content if multiple depths were measured. To examine relationships between soild15N and climate, a non-linear model was used to predict soild15N with MAT, log-transformed MAP, and average soil depth, which included an independently-fit breakpoint for the relationship between MAT and soild15N12. Subsequent models were used to predict the residuals of the relationship between soild15N and [C]. A structural equation model (SEM)43was used to test the relative importance of direct vs. indirect linkages between climate and soild15N. A non-hierarchical model was first developed and then downward stepwise selection was used to generate a hierarchical model that included only significant paths. SEM statistics were calculated in IBM SPSS AMOS version 20.0.0.1 (AMOS Development Corp. Meadville, Pennsylvania, USA). All other stat- istics were computed in JMP 10.0.2 (SAS Institute, Cary, North Carolina, USA).
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Acknowledgments
The authors express their sincere appreciation to the numerous individuals who provided data for this synthesis, especially Stephen Porder, Georg Guggenberger, Robert Mikutta, Valery Terwilliger and Yuanhe Yang. Mac Post, Ben Houlton, Phil Taylor, Sharon Hall, Sharon Billings, and Matt Wallenstein provided helpful advice on earlier versions of this manuscript. Any use of trade names is for descriptive purposes only and does not imply endorsement by the US Government.
Author contributions
J.M.C. designed research and created all figures. J.M.C. and L.W. analysed the data, J.M.C.
led the writing of the paper with substantial input from A.J.E., L.A., W.T.B., E.N.J.B., M.D.C., N.J.H., E.A.H., A.K., K.K., J.M.K., M.C.M., E.M.S., J.R.M., K.K.M., A.M., G.B.N., R.S.O., S.S.P., P.L.P., C.A.Q., A.R., L.A.S., B.A.S., B.L.T., R.A.G.V., W.W., L.W. and B.Z.
Additional information
Competing financial interests:The authors declare no competing financial interests.
How to cite this article:Craine, J.M.et al. Convergence of soil nitrogen isotopes across global climate gradients.Sci. Rep.5, 8280; DOI:10.1038/srep08280 (2015).
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